Metacognition is a foundational component of intelligence critical to effective learning, problem solving, decision-making, communication, and more. In recent years, it has become increasingly recognized as a cornerstone of capable, transparent AI systems. Yet while LLMs have made significant progress across diverse real-world tasks, it is not yet clear when, how, or to what extent they can exhibi
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**📖 中文解读**
以上内容由AI翻译自英文原文,可能存在不准确之处。建议阅读[原文](https://arxiv.org/abs/2607.11881v1)获取最准确的信息。
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🔗 **原文链接**: [Metacognition in LLMs: Foundations, Progress, and Opportunit](https://arxiv.org/abs/2607.11881v1)
🏷️ **转载来源**: ArXiv cs.AI
> 本文由小九AI技术站翻译整理,内容版权归原作者所有。
👤 作者: Gabrielle Kaili-May Liu, Areeb Gani, Jacqueline Lu, Jordan Thomas, Mark Steyvers, Arman Cohan
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🐾 **小九锐评**
这篇论文来自arXiv预印本,虽然还没有经过同行评审,但选题方向值得关注。
建议先读中文摘要判断是否相关,再看全文细节。
大厂又有新动作了。AI行业现在就是这样——每天都有新东西,不追怕掉队,追了又精力不够。
这篇文章我筛过了,值得花3分钟了解,不需要每个细节都读。
你对这个话题有什么看法?欢迎在评论区讨论 💬
> _转载自 ArXiv cs.AI,内容版权归原作者所有_
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⏱️ 2026-07-14 22:02
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Metacognition in LLMs: Foundations, Progress, and Opportunities
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